Process for the correction of distortions in radiological images

ABSTRACT

Process to correct distortion of radiological images by obtaining the image of a regular test chart and assessing the distortions to which the image is subjected. This assessment is used to correct normal images obtained with the installation. One obtains automatically the distortion corrections to be applied to the image elements by eliminating (55) the image background by creating (63) images of similar columns, by labelling (66) the columns detected and by calculating (71) the co-ordinates of the intersections of these columns. The calculation of the intersection co-ordinates is improved by replacing (89) these columns by straight segments whose position is calculated by a regression of least error squares over all the image elements belonging to this column and situated near this intersection. Preferably, all these calculations should be made through implementing mathematical morphology operations.

BACKGROUND OF THE INVENTION

An object of the present invention is a process for the correction ofthe distortion of radiological images acquired with a luminanceintensifier tube. It can be applied more particularly to the medicalfield. It can be implemented either in direct radioscopy or in radiologywith digitized processing of the signal representing the image. Itrelates more particularly to future-generation tomodensitometers inwhich the detection element will be a luminance intensifier device suchas this. Its object is to resolve the problems of morphometry raised bythe use of such tubes.

An intensifier tube of radiological images is designed to receive alow-power X-radiation and to convert this X-radiation into a morepowerful light radiation that can be more easily detected by a displaymeans, especially by a camera. The reason for the weakness of theX-radiation received must be sought in the need to provide protection,especially in medicine, for patients subjected to examinations withradiation of this kind. This is so especially when such examinations arelengthy, as is the case with tomodensitometry processing operations orprocessing with digitization of image information elements.

An image intensifier tube essentially has a conversion panel to converta received X-radiation into a light radiation that is capable ofstriking a photocathode placed in a position where it faces this panel.The conversion of X-radiation into light radiation is obtained in aknown way by providing the panel with caesium iodide crystals. Under theeffect of the X-ray illumination, photoelectrons are liberated from thephotocathode and move towards the screen. This movement towards thescreen is subjected to the effects of an electronic optical system. Thiselectronic optical system tends towards an effect where the impacts ofthe photo-electrons on the screen correspond to the places on thephoto-cathode from which they have been emitted.

The screen is itself of a special type: it re-emits a light imagerepresenting the electronic image conveyed by the electrons, and thisimage itself represents the X-ray image. This light image can then bedisplayed by any display means, especially a standard camera, so as tobe displayed on a display device, especially a device of the televisionmonitor type.

A display system such as this has a major drawback: the revealed imageis an image that is geometrically distorted in relation to the X-rayimage from which it has originated. This distortion occurs essentiallybetween the photo-cathode, excited by the photons emerging from theconversion panel, and the screen that receives the electron radiationemitted by this photo-cathode. Indeed, during their journey, thephoto-electrons are subjected to disturbing effects, notably magneticeffects, due to the earth's magnetic field. If all the photo-electronswere to be affected, during this journey, by one and the same type ofdisturbance, then correcting the effect of these disturbances at anypart of the sequence of images to would be enough to avert problems.Unfortunately, these photo-electrons are highly sensitive todisturbances. And the inhomogeneity of the magnetic field in the placesthrough which they pass is then such as to result in a distortion in theelectronic image projected on the screen.

To give a more concrete explanation of the effects of a distortion suchas this, it may be said that the image of a straight line interposedbetween an X-ray tube and an image intensifier such as this will be astraight line in the X-ray image that excites the panel, it will be astraight line in the photon image that strikes the photo-cathode, and itwill be a straight line in the electron image that leaves thisphoto-cathode, but it will no longer be a straight line in theelectronic image that gets displayed on the screen. Consequently, it canno longer be a straight line in the light image produced by this screen.The display device placed downline then reveals, so to speak, the resultof the distortion due to the non-homogeneity of the earth's magneticfield in the space crossed by the electronic image.

Until now, it has been possible to overlook this type of drawbackbecause the images to be produced have been essentially qualitative andbecause their quantitative content, namely the exactness of the drawingof the contours of the object revealed, has been a matter of littleconcern. However, at present, with the development of techniques, it isincreasingly being sought to use these images quantitatively. Forexample, prosthetic fixtures may have to be made from the imagesobtained. In this case, it would be intolerable to have warped images.Besides, in industrial checking, this type of defect obviates any easyuse of image intensifiers such as these in metrology.

Among the deformations or distortions of the image, attention may bedrawn to the so-called "pincushion" distortion that arises out of thegeometry of the spherical dome of the input face of the tube, namely theupper face of the panel. Attention may also be drawn to the so-called"S" deformation arising out of the deflection of the electronic paths bythe magnetic fields, especially the earth's magnetic field. Thedistortion therefore shows a permanent component, related to a giventube, and a variable component related to the very position of the tubein the earth's magnetic field.

Various processes have been envisaged to reduce the effects of thislatter distortion. A first approach, through technological developments,has tried to reduce the effects of distortion, namely the effects of thedisturbing magnetic fields. To this end, the image intensifier tubeshave been provided with magnetic cladding parts (elements to canalizethe magnetic field) that encase the tube. However, this casing cannotcover the conversion panel, and accordingly, disturbing magnetic effectsare nevertheless exerted in the vicinity of this panel at the positionwhere they are ultimately the most effective owing to the fact that thephoto-electrons liberated from the photo-cathode are moved at very lowspeeds in the vicinity of this panel.

To complete this device, a process has furthermore been devised whereina coil for the production of a compensating magnetic field is positionedin the vicinity of the upper face of the tube. A French patentapplication No. 88 04071, filed on 29 Mar., 1988 has even envisaged theservo-linking of the current flowing through this coil to a measurementof the magnetic field to be compensated for. Despite all its promise,this process gives but imperfect results. The precision of thecorrection of distortion is insufficient in relation to the applicationsenvisaged, for it too cannot be used to eliminate the "pincushion"effect.

Another process of correction of the distortions has been envisaged. Itrelates to a parametrical approach. According to this approach, thedeformations are modelized on the basis of the knowledge of thegeometrical and electro-optical characteristics of the system. Thissuccess of this process is conditioned by the precision with which thesystem to be modelized is known. As an analytical approach, it calls formajor simplifications of the model in order to be capable of beingcomputed. These simplifications are such that, ultimately, this processcan no longer take account of every phenomenon, especially more complexphenomena resulting from the "S" deformation.

OBJECTS AND SUMMARY OF THE INVENTION

An object of the invention is to remedy these drawbacks by proposing anovel process wherein there is carried out the acquisition of images ofa calibrated test chart and wherein the distortion of the image of thistest chart is measured in relation to its expected theoretical shape.This measurement is naturally done for all the useful positions in spaceof the image intensifier tube/X-ray tube assembly. Subsequently, theradiological images acquired are corrected as a function of theassessments of this distortion. This pragmatic and non-parametricalprocess can be used to take account of all the physical phenomena cominginto play in the distortion, as opposed to the known processes where inone way (rough technology) or another (approximate model-building), allthe distortions were not taken into account.

An object of the invention, therefore, is a process for the correctionof the distortion of radiological images acquired with a luminanceintensifier tube, these images comprising a collection of addresses ofimage elements in relation with grey levels assigned to these elements,wherein:

the image of a test chart placed on the input face of this tube isacquired;

an assessment is made of the distortion of this test chart with respectto its expected theoretical shape;

and normal radiological images are corrected as a function of thisassessment.

In one improvement, the acquisition of the real image of a test chart,given the multiplicity of the possible positions in space of theintensifier tube/X-ray tube assembly, is automatic. Furthermore, thisacquisition is done by using a particular test chart, the structure ofwhich is such that it does not itself introduce imprecision into thecorrection computations that are to be deduced from it.

The invention is used especially in systems of digital angiography,where it is desirable to estimate the geometrical deformations in orderto correct the measurements of distance, areas or volumes made on theorgans from the images, but in which it is also valuable to be able toeffectively restore the images. This restoring is useful in thearteriography of the lower limbs, when it is sought to reconstruct a legfrom several juxtaposed images for example.

In generalized tomodensitometry, in the case of 3D reconstruction using2D projections, the correction of the distortions is indispensable andcalls for high precision. The precision comes into play at two instants:during the calibration of the acquisition systems and during therestoring of the images proper, prior to any 3D reconstruction. It couldbe shown that the requisite levels of precision can be obtained with theinvention: i.e. precision of 1/10th of an image element for thecalibration of the acquisition system, and 1/2 of an image element forthe 3D reconstruction from 2D projections. Furthermore, it is possibleto be satisfied with corrections of the order of one pixel forgeometrical measurements on the image.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be understood more clearly from the followingdescription and from the appended figures. These figures are givenpurely by way of an indication and in no way restrict the scope of theinvention. In these figures,

FIG. 1 shows the schematic drawing of a radiological system to implementthe process of the invention;

FIG. 2 shows the drawing of a standard grid that can be used as a testchart;

FIG. 3 shows a graphic representation of operations of mathematicalmorphology, enabling the automatic detection of the image of the testchart;

FIG. 4 shows the schematic drawing of the corrections of distortion tobe applied to restore the images geometrically;

FIG. 5 shows the sequence of the preferred operations implemented in theprocess of the invention;

FIG. 6 shows the effects of a particular processing of the images torender the background stationary and remove background noises;

FIGS. 7a and 7b shows the technological characteristics that lead to thedetermining of the best test chart possible.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 gives a schematic view of an imaging system that can be used toimplement the process of the invention. In this system, an X-ray tube 1emits an X-radiation tube 2 towards an image intensifier tube 3. Theimage intensifier tube 3 is connected to an image processing device 4,which is itself connected to a device 5 for the display of the processedimages. The reading of the distortions undergone by the images for agiven position of the X-ray tube 1/image intensifier tube 3 assembly isgiven by the interposition, prior to any measurement for standard use ofa test chart 6 between this tube 1 and the intensifier 3. Preferably,the test chart 6 has substantially the same dimensions as the input faceof the intensifier 3 and it is paced against this face. In practice, thetest chart 6 comprises a grid pattern (FIG. 2) of horizontal andvertical bars. In a preferred example, the test chart has a roundexternal shape, with a diameter of about 30 cm., and has bars spaced outfrom one another by about one centimeter and having a width of the orderof 1 mm.

During a distortion measuring operation, an image resembling that ofFIG. 3 is recorded in the image memory of the device 4, and it can bedisplayed on the screen of the monitor 5. This image comprises acollection of addresses of memory cells, corresponding to the imageelements or pixels of the image displayed, associated with informationelements representing the grey level. These grey levels can be displayedby the spot of the monitor, on the screen of this monitor, and in thelast analysis they correspond to the luminosity assigned to these imageelements. The bars of the test chart, in this case for example a bar 8,are distorted (exaggeratedly herein).

It is seen that, in addition to the distorted geometrical character ofthe image of the bar 8, this bar is represented by pixels having a highgrey level, for example the pixel 9, and by pixels having a low greylevel, for example the pixels 10 to 14. The latter pixels are depictedby small dots, as opposed to the big dots substantially showing thecenter of the bar 8 at the position of a profile 15 perpendicularlyintersecting the bar 8. On either side of the position of the pixels 10and 14, which have a low grey level, the image memory has image elementswith a grey level that is almost zero (but for the noise). This is shownschematically by the absence of dots at the intersection of the lines 16and 15, symbolizing x-axis and y-axis values (addresses) of imageelements.

FIG. 4 shows, in substance, the main principle of the invention. Asshall be seen hereinafter, it will be possible to make a very precisecomputation of the coordinates, namely the addresses, of all the imageelements representing the centers of the horizontal and vertical bars 17to 22 respectively of the test chart. It will also be shown that it ispossible to make an automatic computation of the addresses of the pointsof intersection 23 to 27 of all the bars with one another. Assuming thatthe test chart occupies a position known in advance, represented forexample by the bars 28 to 34, it becomes possible to compute the shiftsδ, 35 to 39 respectively, to be assigned to the coordinates of the realimage elements that may be located respectively at 23 to 27, to bringthem to locations 40 to 44, where the geometrical distortion may beconsidered to have been eliminated.

For real image elements located at an intermediate position betweenelements such as 23 to 27, a corrective bilinear interpolation isproposed so as to assign them a shift 5 that takes account of theirimmediate surroundings.

An objection may be raised that the position of the test chart 6 on theintensifier 6 is not known, and that ultimately there is no exactknowledge of the positions of the theoretical images 28 to 34 of thesebars nor that of their intersections. However, it may be noted that thegrid itself is known. If we then make the additional assumption that thetest chart 6 is provided with bars distributed in a particular way, forexample regularly, it may be assumed that the shifts δ 35 to 39 areknown, firstly to within plus or minus one whole shift of the pitch ofthe grid and, secondly, to within plus or minus one change of axis. Thischange of axis takes account of the real orientation of the axes of thetest chart in relation to the directions that are arbitrarily assignedto them in the image memory. It will then be noted that these twoapproximations are not a source of trouble since they affect all theimage elements either in the same way or coherently. Indeed, the sametranslation by a whole number of pitches of the grid and the effects ofone and the same change of axes would have to be applied to all thetheoretical intersections 40 to 44.

In FIG. 4, a line of dashes shows, for example, the non-distorted andreal position that should be occupied by the theoretical axes 28 to 29,representing the virtual image of the test chart. All the translationsand changes in axes are represented by the double arrows 45 to 47. It isseen that these double arrows do not necessarily all have the samelength. This ultimately means that the test chart 6 need not necessarilyhave been placed in such a way that its different bars are subsequentlystrictly parallel to image lines and columns of the image memory or ofthe image displayed.

However, it is important to note that if we take the precaution ofacquiring all the positions of the X-ray tube 1/intensifier 3 assembly,with a test chart 6 that is held on the tube 3 is a fixed position thatis constant during the various acquisitions, the effects of thesetranslations (and changes of axes) 45 to 47 will be the same in all theimage. In the ultimate analysis, the way in which the test chart hasbeen placed on the intensifier 3 during these acquisitions ofcorrections will have no influence.

FIG. 5 gives a schematic view of all the steps of the process of theinvention. This shall be explained with reference to FIGS. 6 and 3 whichcorrespond to bars in the digital image contained in the image memory.FIG. 6 shows a line 50 obtained by the exploration of the image memory,for example along a profile such as the profile 15. Addresses (namelyimage elements) are encountered along this profile. The y-axis value ofthese addresses is constant, but their x-axis value varies by one unitfrom one pixel to another, from one image element to another. In firstregions 51, the grey level is high. Indeed, in these regions 51,corresponding to inter-bar spaces, the X-radiation has greatly excitedthe intensifier 3. The corresponding electrical signal detected has beenhigh. By contrast, on either Side, namely 52 and 53, of the middle 54 ofthe bar, for example the bar 8, there are regions where the grey levelfalls. These regions correspond to the locations of the pixels 10 to 14.The middle 54 of the bar, for its part, corresponds schematically to thepixel 9.

It will be noted that the signal shows a variation of its component asand when the profile continues to be explored along the x-axis. Thisdevelopment is related to the presence of a non-stationary imagebackground. This background is ultimately a source of difficulty. Forthis stationary background prevents the implementation of a simpledetection threshold to automatically identify the position of the barsalong the profiles. In the invention, when it is necessary, during anoperation referenced 55 in FIG. 5, the image is made stationary by theapplication to this image, preferably, of a morphological transformationknown as a top hat transformation.

A morphological transformation such as this uses opening and closingtype operations that are transformations proper to the theory ofmathematical morphology. It will be recalled that a closing operation isconstituted by an expansion followed by an erosion. Conversely, anopening is constituted by an erosion followed by an expansion. It willbe recalled that an erosion of an image consists in the creation ofanother image after an exploration in erosion of the basic image. Thebasic image is explored by means of a window having given dimensions anda given geometrical shape and possessing a given center. For example, inthe invention, three preferred types of windows (FIG. 3) are used:firstly, a circular window 56 constituted by a circle with a radius of 5pixels and, secondly, segment windows, 57 and 58 respectively. Thelength of these segments is 9 pixels and their width is only one pixel.It is possible to give these segments 57 and 58 as well as the circle 56a center. This center may be any point of the window. It is preferably apixel located at the geometrical center.

When the basic image is explored with a window, an assessment is made ofthe grey level of all the pixels of this image located vertically tothis window. In a given position of exploration, the grey levels of thepixels vertical to the window may range from α, which is a minimumvalue, and A which is a maximum value. In an erosion operation, it isdecided to assign a grey level equal to α to the element of the image tobe created that has the same coordinates at the center of the window inthe basic image. In an expansion operation, a value A is assigned to thepixel of the image to be created, that has the same coordinates as thepixel vertical to the center of the window. In this case, it is saidthat the erosions and the expansions are done in terms of grey level.The immediate result thereof is that the opening and closing operationsare also done in terms of grey level. By contrast, if the basic imagesare in binary mode, or even if a threshold is defined, below or abovewhich the grey level is considered to be 0 or 1, the closing and openingoperations are done correlatively in binary mode. The geometrical shapeof the exploration window is quite related to the result to be achieved.

If it is assumed that it is sought to obtain 512×512 pixel images withan input face of the image intensifier, the diameter of which istypically of the order of 30 cm, it is deduced therefrom that thedistance between two neighboring pixels is of the order of 0.5 mm. If,as has just been indicated, a circular window is then chosen, with adiameter of ten pixels (5 mm) whereas the width of the image of thebars, even when distorted, is at any rate smaller than ten pixels, it ispossible, with an operation for closing the image, to obtain the contour59 (FIG. 6). For, during the expansion operation of this closing, A isassigned as the grey level to all the window centers, hence to all theelements of the expanded image. If A varies slightly, the slow variationof A is thus preserved. Ultimately, the continuous component of thebackground image, which does not include the peaks 54, has beenrestored. During the next erosion operation of this closing, α isassigned as the grey level to all the elements of the eroded imagecorresponding to the center of the image in the expanded image obtainedbeforehand. It could be shown that this closing operation amounts tofiltering the peaks 54 in such a way as to leave only the contour 59.

If

    CLOSE(I)

designates the expanded and then eroded basic image I, it is realisedthat the basic image can be subtracted, pixel by pixel, from thisexpanded-eroded image. We then obtain the contour 62, also shown in FIG.6, from which the background noise has disappeared. The image 62 istherefore equivalent to the collection (FIG. 5) of the coordinates ofthe pixels placed in relation to their grey level (NG) and madestationary. Hereinafter in this description, this digitized image madestationary shall be called M.

An operation 63 is then used to make a search, in the image M, for theposition of the bars. The search for a bar, when the coordinates of atleast one pixel that definitely belongs to a bar have been found,consists in exploring the grey levels of the immediately neighboringpixels to try and determine whether they belong to the same bar.However, this operation is not facilitated when automatic explorationleads to the position of the intersections of the horizontal andvertical bars. Indeed, there is a risk that the automatic explorationprocess will leave a given type of bar, for example a vertical one, andthen start exploring a bar of another given type, for example ahorizontal bar. To avert this risk, two images are created out of theimage M. A first image includes only the vertical bars, and a secondimage includes only the horizontal bars. To this end, the image M ismade to undergo two opening operations. A first opening operation

    OPEN (M, 57)

can be used to give the image of the opening of the image M (erosionfollowed by expansion) by the segment 57. It is seen that, during theerosion stage corresponding to this opening, all the grey levels of thepixels that are located outside the horizontal bars are cancelled.Indeed, the segment 57 is horizontal and, as soon as this segment nolonger directly explores a horizontal bar, it makes a partialexploration of a vertical bar. And at least one of the pixels verticalto this window then possesses a zero or very low grey level. During theexpansion operation that follows, the pixels of the vertical bars arenot recreated. As a result, the segment 57, during this openingoperation, enables the production of an image of the horizontal barsalone. An image of the horizontal or line bars is characterized by thecollection of the addresses x, Y_(j), the associated grey level of whichis neither zero nor very low. The same opening operation is redone, butwith the segment 58. This time, an image of vertical bars, i.e. columns,is determined, namely the collection of the pixels with coordinatesx_(i), y, the associated grey level of which is not zero.

Ultimately, with these two operations, there is obtained an image oflines or an image of columns in which there is no longer any bridgebetween the lines or between the columns. FIG. 3 shows this point ofview, in which the horizontal bars are no longer shown.

It may be said that, in these images of vertical bars or horizontalbars, we are then dealing with separated sets. In a labelling operation,a column or line number respectively is now assigned to each of thesesets. In practice, this number represents the x-axis value or the y-axisvalue, respectively, of the bar in the virtual image of the test chart.To this end, these column or line images are explored so as to assign anumber to each column or each line. A line number will be a number Y₁,Y₂, or more generally Y_(J) and this line number will be assigned as anadditional dimension to the collection of the pixels, the addresses x,Y_(j) of which have shown that they belong to one and the same set. Forexample, to determine the collection of the pixels X_(i), y belonging tothe bar 8, the information content of the pixels belonging to a profileis explored by moving from left to right. The information content ofeach image element address belonging to this profile is tested.

For example, when the pixel 10 is reached, it is assigned a number. Thisnumber will correspond to the number of the bar No. 8. The pixels 11,12, 9, 13 and 14 are then explored and receive the same number. Thepixel 64 receives no number. Its grey level is too low: it does notbelong to a bar, and nor do the following pixels until pixels with aninformation content resembling that of the pixels 9 to 14 areencountered again on the same profile. In this case, they are assigned acolumn number incremented by one unit. The process is continued in thisway until the right-hand lateral edge of the image. The pixels belongingto each column having been thus marked, each of them is then followedupwards and then downwards in going from one pixel to its neighbor withthe highest grey level. In this journey, its pixels X_(i), y areassigned its number X_(i). Continuing the process in this way, thefollowing are created: the collection 69 of the addresses of the imageelements corresponding to the column Y_(I), the collection 70 of theaddresses of the image elements belonging to the column Y_(I+1) and soon and so forth.

This operation can be repeated by the exploration no longer of thevertical bars 15 but of the horizontal bars. We then obtain thecollections 66, 67 and the following collections of the addresses of theimage elements belonging to lines numbered Y_(J) or X_(J) +1.

An operation 71 is then used to search for the rough positions of theintersections of the bars. These intersections are represented by thecollections of the image elements having addresses X_(i) and Y_(j)corresponding respectively to columns X_(I) and Y_(J) at the same time.Thus, there are obtained the collections 72 to 73 of pixels assigned toeach of the intersections X_(I), Y_(J). In practice, the step 71 may beexecuted at the same time as the pixels of the second group of the barsare determined.

FIGS. 7a and 7b show a specific feature of the test chart enabling adegree of precision in the correction of the distortion to within lessthan a tenth of a pixel. The test chart 6 (FIG. 7b) could be made bymeans of an arrangement of absorbent wires 74, for example made of leador another metal. However, the making of a test chart such as this hastwo drawbacks. Firstly, on the edges 75 and 76 of the wires, the heightcrossed by the X-radiation is smaller than the height crossed at thecenter of these wires. As a consequence, the grey levels detectedcorresponding to positions vertical to these places crossed are nothomogeneous with the grey levels detected vertically to the center ofthe wires 74. Furthermore, the second drawback is that, if they are bemechanically sturdy, the wires should be made with a certain diameter.As a result, saturation of absorption is swiftly reached. In the end,vertically to the central part of the wire 74, the grey level signal isa flat signal 77. It is not possible, with a flat signal such as this,to know the exact position of the center of the wire 74.

In a preferred embodiment, the test chart is made by the photoetching ofa gold layer 78 having a thickness. The thickness of this layer ispreferably 0.050 mm. This photoetching is done on a glass plate. Theadvantage of this approach is that the test chart is almost incapable ofbeing deformed. Furthermore, gold is a material whose use is perfectlymastered in photoetching. The precision that can be obtained inphotoetching with gold is of the order of one to five thousandths of amillimeter. Furthermore, gold is also more absorbent than lead and,hence, a thickness of 0.05 mm is sufficient to prompt a non-saturatedabsorption signal at the commonly used levels of X-ray power. Finally,the photoetching approach can be used to obtain steep flanks 79 ofstrips 8 constituting the bars of the test chart. In this way, thephenomenon of the gradual change in the grey level of the neighboringpixels represents only the X-ray illumination and not any addedparasitic phenomenon. The test chart does not contribute any imprecisionof its own.

FIG. 7a gives a view, according to a given profile, of the grey levelsmeasured for neighboring pixels and corresponding to a column numberedX_(I). In the invention, a search is made for the position of the centerof gravity of the X-ray illumination for each profile. The x-axis valueX_(gi) of this barycenter is computed on the value of the grey levelsNG_(i) according to the following equation:

    X.sub.gi =Σ(X.sub.i.NG.sub.i)/Σ(NG.sub.i).

This enables the determining, in fractions of pixels, of the x-axisvalue of the barycenter 80. The same operation (FIG. 5) 81 of searchingfor the position of the barycenter is done for all the profilesbelonging to one and the same collection. Thus, for example, thebarycenters 82 to 86 for the column X_(I) are obtained. Similarly, otherbarycenters would be obtained for a segment of this line Y_(J) or,rather, for a segment of this line located on the rough position of theintersection of the bars.

Then, an equation of an y=ax+b type is computed for a straight line,known as a least error squares straight regression line, wherein the sumof the distances such as 88, squared, from this straight line to thebarycenters found is as small as possible. These computations are of aknown type, and are such that:

    a=(NΣx.sub.j.Y.sub.j -Σx.sub.j.ΣY.sub.j)/σ

    b=(Σx.sub.j.sup.2.ΣY.sub.j -Σx.sub.j.Y.sub.j.Σx.sub.j)/σ

where N is the number of points of the regression, and where σ is givenby:

    σ=NΣx.sub.j.sup.2 -(Σx.sub.j).sup.2.

Once the equation of the image 87 of the center of a bar is known, thesame operation is recommenced for all the other segments, vertical orhorizontal, of the image. The result of these operations 89 is acollection of coefficients (a₁, a₂, b₁, b₂) parametrizing segmentscorresponding to the intersections of the columns X_(I) and Y_(J). In asubsequent operation 90, of an analytical type, a computation is made ofthe coordinates of the points of intersection of the segments 87 whichintersect one another. The coordinates of these intersections correspondultimately to the coordinates 23 to 27 (FIG. 4) of the distorted imageof the test chart. These coordinates of intersections are alsoassociated with the pairs of coordinates X_(I) and X_(J) of theintersections of the test chart. Now these intersections, given theprecision with which the test chart is made, are known in advance. Forexample, these coordinates are obtained by multiplying the number of thecolumn by the pitch (measured by the test chart) of the test chart atthe corresponding position. To simplify matters, it may be said that itis possible to compute the correction vectors such as 35 to 39 bydeducting the values X.sub. i and Y_(J) from the computed values of thecoordinates of the points of intersection of the bars of the test chart.

The correction of the geometrical deformations of the images is thenundertaken preferably by bilinear interpolation. A bilinear correctionconsists in computing the correction of distortion to be assigned to apixel identified in a 2D mesh as a function of the corrections ofdistortion to be applied to each of the vertices of the mesh. Thecorrections of the vertices are combined with one another by means of aweighting that takes account of the relative distance of the pixel fromeach of the vertices. It will be noted, however, that since thecorrections of distortion of the vertices of the meshes of the testchart are given in fractions of a pixel, it is most often the case thatthe corrected coordinates of the pixels of the acquired image also fallbetween four pixels. This pixel can then be made to undergo a greycorrection. This restoring is done by means of a second bilinearcorrection in taking account of four corrected pixels that surround apixel of the image to be displayed.

We claim:
 1. A process for the correction of the distortion ofradiological images acquired with a luminance intensifier tube, saidimages comprising a collection of addresses of image elements inrelation with grey levels assigned to said elements, said processcomprising:acquiring a real image of a test chart, formed by horizontaland vertical bars, said this test chart being placed in front of theinput face of said tube, assessing the distortion of said test chartwith respect to its expected theoretical shape, and correcting saidradiological images as a function of said assessment, wherein saidassessing step includes automatically detecting the position of controlpixels bysearching, by operations of mathematical morphology, for thepositions of bars of each of two types, following and labelling saidbars, and localizing and labelling points of intersection of said barsof said two types, and assessing localized shifts of said points ofintersection.
 2. A process according to claim 1, wherein operations ofmathematical morphology are carried out in terms of grey level.
 3. Aprocess according to claim 1 or claim 2 wherein said searching stepcomprises making the background of the image stationary by an operationof mathematical morphology.
 4. A process according to claim 1, whereinsaid searching step comprises creating images of bars of each of saidtwo types.
 5. A process according to claim 1, wherein said step ofassessing said shifts comprisesestimating the position of a controlpixel in the image by the intersection of two selected straight segmentseach belonging to a selected bar in the vicinity of said control pixel.6. A process according to claim 5, further comprising selecting saidsegments, said selecting step includingcomputing, along said selectedbar, and for image elements aligned along a profile perpendicular tosaid selected bar, the position of barycenters in terms of grey level,and approximating the position of all the barycenters by a segment fromwhich the sum of the distances to barycenters squared is the lowest. 7.A process according to claim 1 wherein said correcting stepcomprisescomputing, by bilinear interpolation between four estimatedcontrol pixels surrounding any pixel, the shifts of coordinates to beassigned to said pixel.
 8. A process according to claim 1, wherein saidcorrecting step further comprisesrestoring the grey level of an imageelement by bilinear interpolation on a neighborhood of four neighboringimage elements.
 9. A process according to claim 1, further comprisingreiterating said process for various positions of the tube in the spaceof the screen while leaving the test chart in the same place on saidtube.
 10. A process according to claim 1, wherein said test chartcomprises a substrate on which a layer of gold is photo-etched, saidgold layer having a thickness of about 50 micrometers.
 11. A processaccording to claim 1, wherein said test chart comprises a regular gridpattern of bars formed from etched metal strips having a width of aboutone millimeter and being spaced from one another by a distance of about10 millimeters.
 12. A process according to claim 1, further comprisingthe step of displaying the corrected radiological images.
 13. A processfor the correction of the distortion of radiological images acquiredwith a luminance intensifier tube, said images comprising a collectionof addresses of image elements in relation with grey levels assigned tosaid image elements, said process comprising:(A) acquiring a real imageof a movable test chart placed in front of an input face of saidintensifier tube, said test chart comprising a substrate on which isphoto-etched a metal layer, said test chart having an expectedtheoretical shape; (B) assessing the distortion of said real image ofsaid test chart with respect to said expected theoretical shape; and (C)correcting said radiological images as a function of said assessment.14. A process according to claim 13, wherein said test chart comprises asubstrate on which a layer of gold is photo-etched, said gold layerhaving a thickness of about 50 micrometers.
 15. A process according toclaim 13, wherein said test chart comprises a regular grid pattern ofbars formed from etched metal strips having a width of about onemillimeter and being spaced from one another by a distance of about 10millimeters.
 16. A process according to claim 13, wherein said testchart includes a plurality of bars, and wherein said assessing stepcomprises(1) searching, using mathematical morphology, for the positionsof bars of each of two types; (2) following and labelling the two typesof bars located in said step (1); and (3) localizing and labellingpoints of intersection of bars of said two types; and (4) assessinglocalized shifts of said points of intersection.
 17. A process accordingto claim 13, further comprising the step of displaying the correctedradiological images.
 18. A process for the correction of the distortionof radiological images acquired with a luminance intensifier tube, saidimages comprising a collection of addresses of image elements inrelation with grey levels assigned to said image elements, said processcomprising:(A) acquiring a real image of a movable test chart placed infront of an input face of said intensifier tube, said test chartcomprising a substrate on which is photo-etched a layer of gold having athickness of about 50 micrometers, said test chart having an expectedtheoretical shape; (B) assessing the distortion of said real image ofsaid test chart with respect to said expected theoretical shape; and (C)correcting said radiological images as a function of said assessment;wherein said assessing step includes(1) searching, using mathematicalmorphology, for the positions of bars of said test chart of each of twotypes; (2) following and labelling the two types of bars located in saidstep (1); and (3) localizing and labelling points of intersection ofbars of said two types; and (4) assessing localized shifts of saidpoints of intersection, said step of assessing said localized shiftsincluding estimating the position of a control pixel in the image bylocating the intersection of two selected straight segments eachbelonging to a selected bar in the vicinity of said control pixel; and(D) displaying said corrected radiological images.
 19. A processaccording to claim 18, further comprising selecting said segments, saidselecting step including(1) computing, along said selected bar, and forimage elements aligned with a profile perpendicular to said selectedbar, the positions of barycenters in terms of grey level, and (2)approximating the position of all of said barycenters by computing asegment the sum of the square of the distances from the barycenters towhich is the lowest.
 20. A process as defined in claim 18, wherein saidcorrecting step further comprises restoring the grey level of an imageelement by bilinear interpolation on a neighborhood of four neighboringimage elements.